Self-supervised Self2Self denoising strategy for OCT speckle reduction with a single noisy image.

Optical coherence tomography (OCT) inevitably suffers from the influence of speckles originating from multiple scattered photons owing to its low-coherence interferometry property. Although various deep learning schemes have been proposed for OCT despeckling, they typically suffer from the requirement for ground-truth images, which are difficult to collect in clinical practice. To alleviate the influences of speckles without requiring ground-truth images, this paper presents a self-supervised deep learning scheme, namely, Self2Self strategy (S2Snet), for OCT despeckling using a single noisy image. Specifically, in this study, the main deep learning architecture is the Self2Self network, with its partial convolution being updated with a gated convolution layer. Specifically, both the input images and their Bernoulli sampling instances are adopted as network input first, and then, a devised loss function is integrated into the network to remove the background noise. Finally, the denoised output is estimated using the average of multiple predicted outputs. Experiments with various OCT datasets are conducted to verify the effectiveness of the proposed S2Snet scheme. Results compared with those of the existing methods demonstrate that S2Snet not only outperforms those existing self-supervised deep learning methods but also achieves better performances than those non-deep learning ones in different cases. Specifically, S2Snet achieves an improvement of 3.41% and 2.37% for PSNR and SSIM, respectively, as compared to the original Self2Self network, while such improvements become 19.9% and 22.7% as compared with the well-known non-deep learning NWSR method.

Magnetic microspheres enhanced peanut structure cascaded lasso shaped fiber laser biosensor for cancer marker-CEACAM5 detection in serum.

The detection of trace cancer markers in body fluids such as blood/serum is crucial for cancer diseases screening and treatment, which requires high sensitivity and specificity of biosensors. In this study, a peanut structure cascaded lasso (PSCL) shaped fiber sensing probe based on fiber laser demodulation method was proposed to specifically detect the carcinoembryonic antigen related cell adhesion molecules 5 (CEACAM5) protein in serum. Thanks for the narrow linewidth and high signal-to-noise ratio (SNR) of the laser spectrum, it is easier to distinguish small spectral changes than interference spectrum. Adding the antibody modified magnetic microspheres (MMS) to form the sandwich structure of "antibody-antigen-antibody-MMS", and amplified the response caused by biomolecular binding. The limit of detection (LOD) for CEACAM5 in buffer could reach 0.11 ng/mL. Considering the common threshold of 5 ng/mL for CEA during medical screening and the cut off limit of 2.5 ng/mL for some kits, the LOD of proposed biosensor meets the actual needs. Human serum samples from a hospital were used to validate the real sensing capability of proposed biosensor. The deviation between the measured value in various serum samples and the clinical value ranged from 1.9 to 9.8 %. This sensing scheme holds great potential to serve as a point of care testing (POCT) device and extend to more biosensing applications.

Aurora kinase A-mediated phosphorylation triggers structural alteration of Rab1A to enhance ER complexity during mitosis.

Morphological rearrangement of the endoplasmic reticulum (ER) is critical for metazoan mitosis. Yet, how the ER is remodeled by the mitotic signaling remains unclear. Here, we report that mitotic Aurora kinase A (AURKA) employs a small GTPase, Rab1A, to direct ER remodeling. During mitosis, AURKA phosphorylates Rab1A at Thr75. Structural analysis demonstrates that Thr75 phosphorylation renders Rab1A in a constantly active state by preventing interaction with GDP-dissociation inhibitor (GDI). Activated Rab1A is retained on the ER and induces the oligomerization of ER-shaping protein RTNs and REEPs, eventually triggering an increase of ER complexity. In various models, from Caenorhabditis elegans and Drosophila to mammals, inhibition of Rab1AThr75 phosphorylation by genetic modifications disrupts ER remodeling. Thus, our study reveals an evolutionarily conserved mechanism explaining how mitotic kinase controls ER remodeling and uncovers a critical function of Rab GTPases in metaphase.

A Multimode Microfiber Specklegram Biosensor for Measurement of CEACAM5 through AI Diagnosis.

Carcinoembryonic antigen (CEACAM5), as a broad-spectrum tumor biomarker, plays a crucial role in analyzing the therapeutic efficacy and progression of cancer. Herein, we propose a novel biosensor based on specklegrams of tapered multimode fiber (MMF) and two-dimensional convolutional neural networks (2D-CNNs) for the detection of CEACAM5. The microfiber is modified with CEA antibodies to specifically recognize antigens. The biosensor utilizes the interference effect of tapered MMF to generate highly sensitive specklegrams in response to different CEACAM5 concentrations. A zero mean normalized cross-correlation (ZNCC) function is explored to calculate the image matching degree of the specklegrams. Profiting from the extremely high detection limit of the speckle sensor, variations in the specklegrams of antibody concentrations from 1 to 1000 ng/mL are measured in the experiment. The surface sensitivity of the biosensor is 0.0012 (ng/mL)-1 within a range of 1 to 50 ng/mL. Moreover, a 2D-CNN was introduced to solve the problem of nonlinear detection surface sensitivity variation in a large dynamic range, and in the search for image features to improve evaluation accuracy, achieving more accurate CEACAM5 monitoring, with a maximum detection error of 0.358%. The proposed fiber specklegram biosensing scheme is easy to implement and has great potential in analyzing the postoperative condition of patients.

Compact optical fiber sensor based on Vernier effect with speckle patterns.

We propose a Vernier effect-based sensor for temperature and salinity measurements. This sensor utilizes the correlation speckle pattern generated by spatial multimode interference and has undergone testing to validate its effectiveness. The speckle demodulation method is used to solve the problem of inconsistent envelope measurement when tracking with different upper and lower envelopes. The device consists of two Fabry Perot interferometers (FPIs) created by connecting hole core fiber (HCF) and erbium-doped fiber (EDF) in series. The speckle image produced by the interferometers is analyzed using the Zero means normalized cross-correlation (ZNCC) technique. The ZNCC value demonstrates a linear relationship with salinity and temperature, allowing for the measurement of these parameters. The sensor exhibits a temperature detection sensitivity of -0.0224 /°C and a salinity detection sensitivity of -0.0439/%. The sensor offers several advantageous features, including its compact size, low-cost manufacturing, high sensitivity, stability, and convenient reflection measurements. These characteristics make it a valuable tool for various applications. The proposed Vernier effect-based temperature and salinity sensor shows great potential for simultaneous monitoring and measurement of temperature and salinity in environments such as marine settings or industrial processes where accurate control of these parameters is crucial.

Loss-balanced parallel decoding network for retinal fluid segmentation in OCT.

As a leading cause of blindness worldwide, macular edema (ME) is mainly determined by sub-retinal fluid (SRF), intraretinal fluid (IRF), and pigment epithelial detachment (PED) accumulation, and therefore, the characterization of SRF, IRF, and PED, which is also known as ME segmentation, has become a crucial issue in ophthalmology. Due to the subjective and time-consuming nature of ME segmentation in retinal optical coherence tomography (OCT) images, automatic computer-aided systems are highly desired in clinical practice. This paper proposes a novel loss-balanced parallel decoding network, namely PadNet, for ME segmentation. Specifically, PadNet mainly consists of an encoder and three parallel decoder modules, which serve as segmentation, contour, and diffusion branches, and they are employed to extract the ME's characteristics, the contour area features, and to expand the ME area from the center to edge, respectively. A new loss-balanced joint-loss function with three components corresponding to each of the three parallel decoding branches is also devised for training. Experiments are conducted with three public datasets to verify the effectiveness of PadNet, and the performances of PadNet are compared with those of five state-of-the-art methods. Results show that PadNet improves ME segmentation accuracy by 8.1%, 11.1%, 0.6%, 1.4% and 8.3%, as compared with UNet, sASPP, MsTGANet, YNet, RetiFluidNet, respectively, which convincingly demonstrates that the proposed PadNet is robust and effective in ME segmentation in different cases.

Spatially Modulated Fiber Speckle for High-Sensitivity Refractive Index Sensing.

A fiber speckle sensor (FSS) based on a tapered multimode fiber (TMMF) has been developed to measure liquid analyte refractive index (RI) in this work. By the lateral and axial offset of input light into TMMF, several high-order modes are excited in TMMF, and the speckle pattern is spatially modulated, which affects an asymmetrical speckle pattern with a random intensity distribution at the output of TMMF. When the TMMF is immersed in the liquid analyte with RI variation, it influences the guided modes, as well as the mode interference, in TMMF. A digital image correlations method with zero-mean normalized cross-correlation coefficient is explored to digitize the speckle image differences, analyzing the RI variation. It is found that the lateral- and axial-offsets-induced speckle sensor can enhance the RI sensitivity from 6.41 to 19.52 RIU-1 compared to the one without offset. The developed TMMF speckle sensor shows an RI resolution of 5.84 × 10-5 over a linear response range of 1.3164 to 1.3588 at 1550 nm. The experimental results indicate the FSS provides a simple, efficient, and economic approach to RI sensing, which exhibits an enormous potential in the image-based ocean-sensing application.

Integrated Fiber Ring Laser Temperature Sensor Based on Vernier Effect with Lyot-Sagnac Interferometer.

The Vernier effect created using an incorporated Lyot-Sagnac loop is used to create an ultra-high sensitivity temperature sensor based on a ring laser cavity. Unlike standard double Sagnac loop systems, the proposed sensor is fused into a single Sagnac loop by adjusting the welding angle between two polarization-maintaining fibers (PMFs) to achieve effective temperature sensitivity amplification. The PMFs are separated into two arms of 0.8 m and 1 m in length, with a 45° angle difference between the fast axes. The sensor's performance is examined both theoretically and experimentally. The experimental results reveal that the Vernier amplification effect can be achieved via PMF rotating shaft welding. The temperature sensitivity in the laser cavity can reach 2.391 nm/°C, which is increased by a factor of more than eight times compared with a single Sagnac loop structure (0.298 nm/°C) with a length of 0.8 m without the Vernier effect at temperatures ranging from 20 °C to 30 °C. Furthermore, unlike traditional optical fiber sensing that uses a broadband light source (BBS) for detection, which causes issues such as low signal-to-noise ratio and broad bandwidth, the Sagnac loop can be employed as a filter by inserting itself into the fiber ring laser (FRL) cavity. When the external parameters change, the laser is offset by the interference general modulation, allowing the external temperature to be monitored. The superior performance of signal-to-noise ratios of up to 50 dB and bandwidths of less than 0.2 nm is achieved. The proposed sensor has a simple structure and high sensitivity and is expected to play a role in biological cell activity monitoring.

Fiber Laser-Based Lasso-Shaped Biosensor for High Precision Detection of Cancer Biomarker-CEACAM5 in Serum.

Detection of trace tumor markers in blood/serum is essential for the early screening and prognosis of cancer diseases, which requires high sensitivity and specificity of the assays and biosensors. A variety of label-free optical fiber-based biosensors has been developed and yielded great opportunities for Point-of-Care Testing (POCT) of cancer biomarkers. The fiber biosensor, however, suffers from a compromise between the responsivity and stability of the sensing signal, which would deteriorate the sensing performance. In addition, the sophistication of sensor preparation hinders the reproduction and scale-up fabrication. To address these issues, in this study, a straightforward lasso-shaped fiber laser biosensor was proposed for the specific determination of carcinoembryonic antigen (CEA)-related cell adhesion molecules 5 (CEACAM5) protein in serum. Due to the ultra-narrow linewidth of the laser, a very small variation of lasing signal caused by biomolecular bonding can be clearly distinguished via high-resolution spectral analysis. The limit of detection (LOD) of the proposed biosensor could reach 9.6 ng/mL according to the buffer test. The sensing capability was further validated by a human serum-based cancer diagnosis trial, enabling great potential for clinical use. The high reproduction of fabrication allowed the mass production of the sensor and extended its utility to a broader biosensing field.

Self-supervised Blind2Unblind deep learning scheme for OCT speckle reductions.

As a low-coherence interferometry-based imaging modality, optical coherence tomography (OCT) inevitably suffers from the influence of speckles originating from multiply scattered photons. Speckles hide tissue microstructures and degrade the accuracy of disease diagnoses, which thus hinder OCT clinical applications. Various methods have been proposed to address such an issue, yet they suffer either from the heavy computational load, or the lack of high-quality clean images prior, or both. In this paper, a novel self-supervised deep learning scheme, namely, Blind2Unblind network with refinement strategy (B2Unet), is proposed for OCT speckle reduction with a single noisy image only. Specifically, the overall B2Unet network architecture is presented first, and then, a global-aware mask mapper together with a loss function are devised to improve image perception and optimize sampled mask mapper blind spots, respectively. To make the blind spots visible to B2Unet, a new re-visible loss is also designed, and its convergence is discussed with the speckle properties being considered. Extensive experiments with different OCT image datasets are finally conducted to compare B2Unet with those state-of-the-art existing methods. Both qualitative and quantitative results convincingly demonstrate that B2Unet outperforms the state-of-the-art model-based and fully supervised deep-learning methods, and it is robust and capable of effectively suppressing speckles while preserving the important tissue micro-structures in OCT images in different cases.

Genetic polymorphisms in genes regulating cell death and prognosis of patients with rectal cancer receiving postoperative chemoradiotherapy.

OBJECTIVE: The identification of biomarkers for predicting chemoradiotherapy efficacy is essential to optimize personalized treatment. This study determined the effects of genetic variations in genes involved in apoptosis, pyroptosis, and ferroptosis on the prognosis of patients with locally advanced rectal cancer receiving postoperative chemoradiotherapy (CRT). METHODS: The Sequenom MassARRAY was used to detect 217 genetic variations in 40 genes from 300 patients with rectal cancer who received postoperative CRT. The associations between genetic variations and overall survival (OS) were evaluated using hazard ratios (HRs) and 95% confidence intervals (CIs) computed using a Cox proportional regression model. Functional experiments were performed to determine the functions of the arachidonate 5-lipoxygenase (ALOX5) gene and the ALOX5 rs702365 variant. RESULTS: We detected 16 genetic polymorphisms in CASP3, CASP7, TRAILR2, GSDME, CASP4, HO-1, ALOX5, GPX4, and NRF2 that were significantly associated with OS in the additive model (P < 0.05). There was a substantial cumulative effect of three genetic polymorphisms (CASP4 rs571407, ALOX5 rs2242332, and HO-1 rs17883419) on OS. Genetic variations in the CASP4 and ALOX5 gene haplotypes were associated with a higher OS. We demonstrated, for the first time, that rs702365 [G] > [C] represses ALOX5 transcription and corollary experiments suggested that ALOX5 may promote colon cancer cell growth by mediating an inflammatory response. CONCLUSIONS: Polymorphisms in genes regulating cell death may play essential roles in the prognosis of patients with rectal cancer who are treated with postoperative CRT and may serve as potential genetic biomarkers for individualized treatment.

Single-cell HER2 quantification via instant signal amplification in microdroplets.

Accurate and ultrasensitive evaluation of human epidermal growth factor receptor 2 (HER2) protein is key to early diagnosis and subtype differentiation of breast cancer. Single-cell analyses to reduce ineffective targeted therapies due to breast cancer heterogeneity and improve patient survival remain challenging. Herein, we reported a novel droplet microfluidic combined with an instant cation exchange signal amplification strategy for quantitative analysis of HER2 protein expression on single cells. In the 160 µm droplets produced by a tapered capillary bundle, abundant Immuno-CdS labeled on HER2-positive cells were replaced by Ag + to obtain Cd2+ that stimulated Rhod-5N fluorescence. This uniformly distributed and instantaneous fluorescence amplification strategy in droplets improves sensitivity and reduces signal fluctuation. Using HER2 modified PS microsphere to simulate single cells, we obtained a linear fitting of HER2-modified concentration and fluorescence intensity in microdroplets with the limit detection of 11.372 pg mL-1. Moreover, the relative standard deviation (RSD) was 4.2-fold lower than the traditional immunofluorescence technique (2.89% vs 12.21%). The HER2 protein on SK-BR-3 cells encapsulated in droplets was subsequently quantified, ranging from 9862.954 pg mL-1 and 205.26 pg mL-1, equivalent to 9.795 × 106 and 2.038 × 105 protein molecules. This detection system provides a universal platform for single-cell sensitive quantitative analysis and contributes to the evaluation of HER2-positive tumors.

Erratum: CHL1 suppresses tumor growth and metastasis in nasopharyngeal carcinoma by repressing PI3K/AKT signaling pathway via interaction with Integrin ß1 and Merlin: Erratum.

[This corrects the article DOI: 10.7150/ijbs.34785.].

Rapid coherent Raman hyperspectral imaging based on delay-spectral focusing dual-comb method and deep learning algorithm.

Rapid coherent Raman hyperspectral imaging shows great promise for applications in sensing, medical diagnostics, and dynamic metabolism monitoring. However, the spectral acquisition speed of current multiplex coherent anti-Stokes Raman scattering (CARS) microscopy is generally limited by the spectrometer integration time, and as the detection speed increases, the signal-to-noise ratio (SNR) of single spectrum will decrease, leading to a terrible imaging quality. In this Letter, we report a dual-comb coherent Raman hyperspectral microscopy imaging system developed by integrating two approaches, a rapid delay-spectral focusing method and deep learning. The spectral refresh rate is exploited by focusing the relative delay scanning in the effective Raman excitation region, enabling a spectral acquisition speed of 36 kHz, ≈4 frames/s, for a pixel resolution of 95 × 95 pixels and a spectral bandwidth no less than 200 cm-1. To improve the spectral SNR and imaging quality, the deep learning models are designed for spectral preprocessing and automatic unsupervised feature extraction. In addition, by changing the relative delay focusing region of the comb pairs, the detected spectral wavenumber region can be flexibly tuned to the high SNR region of the spectrum.

Dynamic wavelength calibration based on synchrosqueezed wavelet transform.

With the developments of the tunable laser source (TLS), there are increasing demands for high-resolution dynamic wavelength calibration in recent years. Considering mutual constraints between wide measurement range and high calibration resolution, we propose a dynamic wavelength calibration method based on an auxiliary Mach-Zehnder interferometer (MZI) and the synchrosqueezed wavelet transform (SSWT). Our proposed method can achieve a calibration resolution of 5 fm and a tuning range of 10 nm. Moreover, the measurement range and spatial resolution of the optical frequency domain reflectometer (OFDR) system are improved to ∼80 m and ∼mm, respectively. Our proposed approach can substantially reduce the subtle spectrum distortion (tens of fm) in coherent optical spectrum analyzer (COSA) systems.

Unique molecular characteristics of NAFLD-associated liver cancer accentuate ß-catenin/TNFRSF19-mediated immune evasion.

BACKGROUND & AIMS: The hepatic manifestation of the metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), can lead to the development of hepatocellular carcinoma (HCC). Despite a strong causative link, NAFLD-HCC is often underrepresented in systematic genome explorations. METHODS: Herein, tumor-normal pairs from 100 patients diagnosed with NAFLD-HCC were subject to next-generation sequencing. Bioinformatic analyses were performed to identify key genomic, epigenomic and transcriptomic events associated with the pathogenesis of NAFLD-HCC. Establishment of primary patient-derived NAFLD-HCC culture was used as a representative human model for downstream in vitro investigations of the underlying CTNNB1 S45P driver mutation. A syngeneic immunocompetent mouse model was used to further test the involvement of CTNNB1mutand TNFRSF19 in reshaping the tumor microenvironment. RESULTS: Mutational processes operative in the livers of patients with NAFLD inferred susceptibility to tumor formation through defective DNA repair pathways. Dense promoter mutations and dysregulated transcription factors accentuated activated transcriptional regulation in NAFLD-HCC, in particular the enrichment of MAZ-MYC activities. Somatic events common in HCCs arising from NAFLD and viral hepatitis B infection underscore similar driver pathways, although an incidence shift highlights CTNNB1mut dominance in NAFLD-HCC (33%). Immune exclusion correlated evidently with CTNNB1mut. Chromatin immunoprecipitation-sequencing integrated with transcriptome and immune profiling revealed a unique transcriptional axis, wherein CTNNB1mut leads to an upregulation of TNFRSF19 which subsequently represses senescence-associated secretory phenotype-like cytokines (including IL6 and CXCL8). This phenomenon could be reverted by the Wnt-modulator ICG001. CONCLUSIONS: The unique mutational processes in the livers of patients with NAFLD and NAFLD-HCC allude to a "field effect" involving a gain-of-function role of CTNNB1 mutations in immune exclusion. LAY SUMMARY: The increasing prevalence of metabolic syndrome in adult populations means that NAFLD is poised to be the major cause of liver cancer in the 21st century. We showed a strong "field effect" in the livers of patients with NAFLD, wherein activated ß-catenin was involved in reshaping the tumor-immune microenvironment.

Low shear stress induced vascular endothelial cell pyroptosis by TET2/SDHB/ROS pathway.

Vascular endothelial cell (VEC) inflammation induced by low shear stress plays key roles in the initiation and progression of atherosclerosis (As). Pyroptosis is a form of inflammatory programmed cell death that is critical for As. However, the effect of low shear stress on VEC pyroptosis and the underlying mechanisms were not clear. Here we show that low shear stress promoted VEC pyroptosis and reduced the expression of Ten-Eleven Translocation 2 (TET2) methylcytosine dioxygenase. Loss of TET2 resulted in the upregulation of the expression and activity of mitochondrial respiratory complex II subunit succinate dehydrogenase B (SDHB) by decreasing the recruitment of histone deacetylase 2, independent of DNA demethylation modification. The overexpression of SDHB mediated mitochondrial injury and increased the production of reactive oxygen species (ROS). The administration of ROS scavenger NAC alleviated VEC pyroptosis induced by SDHB overexpression and TET2 shRNA. These findings show that low shear stress induced endothelial cell pyroptosis through the TET2/SDHB/ROS pathway and offer new insights into As.

PIM2 promotes hepatocellular carcinoma tumorigenesis and progression through activating NF-κB signaling pathway.

Inflammatory factors and activation of oncogenes both played critical roles in the development and progression of human hepatocellular carcinoma (HCC). However, the interplay between these two has not been well studied. In this study, we found that regulated by TNFα, Pim-2 proto-oncogene, serine/threonine kinase (PIM2) was highly expressed in HCC and correlated with poor prognosis (P = 0.007) as well as tumor recurrence (P = 0.014). Functional studies showed that PIM2 could enhance abilities of cell proliferation, cell motility, angiogenesis, chemo-resistance, and in vivo tumorigenicity and HCC metastasis. Mechanistic studies revealed that PIM2 could activate NF-κB signaling pathway through upregulating phosphorylation level of RIPK2. Interestingly, TNFα treatment could induce the expression of PIM2, and overexpression of PIM2 could in turn upregulate the expression of TNFα in HCC cells. More importantly, we found the expression level of PIM2 increased with the progression of liver cirrhosis, and PIM kinase inhibitor AZD1208 treatment could effectively attenuate HCC cells' tumorigenic ability both in vitro and in vivo. Collectively, our study revealed the interaction between an inflammatory factor and a proto-oncogene that contributed to tumorigenesis and progression of HCC, and PIM kinase inhibition may serve as a therapeutic target in the treatment of HCC.

Chromosomal translocation-derived aberrant Rab22a drives metastasis of osteosarcoma.

Osteosarcoma is a type of aggressive malignant bone tumour that frequently metastasizes to lungs, resulting in poor prognosis. However, the molecular mechanisms of lung metastasis of osteosarcoma remain poorly understood. Here we identify exon-intron fusion genes in osteosarcoma cell lines and tissues. These fusion genes are derived from chromosomal translocations that juxtapose the coding region for amino acids 1-38 of Rab22a (Rab22a1-38) with multiple inverted introns and untranslated regions of chromosome 20. The resulting translation products, designated Rab22a-NeoFs, acquire the ability to drive lung metastasis of osteosarcoma. The Rab22a1-38 moiety governs the function of Rab22a-NeoFs by binding to SmgGDS-607, a GTP-GDP exchange factor of RhoA. This association facilitates the release of GTP-bound RhoA from SmgGDS-607, which induces increased activity of RhoA and promotes metastasis. Disrupting the interaction between Rab22a-NeoF1 and SmgGDS-607 with a synthetic peptide prevents lung metastasis in an orthotopic model of osteosarcoma. Our findings may provide a promising strategy for a subset of osteosarcoma patients with lung metastases.